Pareto-Based Optimization of Multicast Flows with QoS and Traffic Engineering Requirements

Abstract

Multicast routing consists in sending information in computer networks to a selective number of destinations. QoS and Traffic Engineering requirements can also be considered in such kind of routing, leading to the need of optimizing a set of objectives subject to constraints. We investigated algorithms to perform the calculus of multicast routes while minimizing four objectives - maximum link utilization, total cost, maximum end-to-end delay and mean end-to-end delay - attending a link capacity constraint. New multiobjective evolutionary models to tackle multicast routing are discussed here based on SPEA2. Besides, two heuristics for subtrees reconnection to be used on crossover and mutation operators are investigated. The first heuristic uses a shortest path algorithm; the second one employs a random search. Our results indicate that the evolutionary model based on SPEA2 using the random search heuristic returned the best performance. The advantage of such approach is observed by comparing the routes obtained using our multiobjective environment with those returned by SPT.